Anna V. Kononova – författare

The  87 revised full papers were carefully reviewed and selected from numerous submissions. The conference presents a study of computing methods derived from natural models. Amorphous Computing, Artificial Life, Artificial Ant Systems, Artificial Immune Systems, Artificial Neural Networks, Cellular Automata, Evolutionary Computation, Swarm Computing, Self-Organizing Systems, Chemical Computation, Molecular Computation, Quantum Computation, Machine Learning, and Artificial Intelligence approaches using Natural Computing methods are just some of the topics covered in this field.

The  87 revised full papers were carefully reviewed and selected from numerous submissions. The conference presents a study of computing methods derived from natural models. Amorphous Computing, Artificial Life, Artificial Ant Systems, Artificial Immune Systems, Artificial Neural Networks, Cellular Automata, Evolutionary Computation, Swarm Computing, Self-Organizing Systems, Chemical Computation, Molecular Computation, Quantum Computation, Machine Learning, and Artificial Intelligence approaches using Natural Computing methods are just some of the topics covered in this field.

This book constitutes the refereed proceedings of the 12th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2022 held in Leiden, The Netherlands, during March 20-24, 2023.

The 44 regular papers presented in this book were carefully reviewed and selected from 65 submissions.

The papers are divided into the following topical sections: Algorithm Design and Engineering; Machine Learning and Multi-criterion Optimization; Benchmarking and Performance Assessment; Indicator Design and Complexity Analysis; Applications in Real World Domains; and Multi-Criteria Decision Making and Interactive Algorithms..

This multi-volume LNCS set, LNCS 15148-15151, constitutes the refereed proceedings of the 18th International Conference on Parallel Problem Solving from Nature, PPSN 2024, held in Hagenberg, Austria, in September 2024.

The 101 full papers presented in these proceedings were carefully reviewed and selected from 294 submissions. The papers presented in these four volumes are organized in the following topical sections:

Part I: Combinatorial Optimization; Genetic Programming; Fitness Landscape Modeling and Analysis.

Part II: Benchmarking and Performance Measures; Automated Algorithm Selection and Configuration; Numerical Optimization; Bayesian- and Surrogate-Assisted Optimization.

Part III: Theoretical Aspects of Nature-Inspired Optimization; (Evolutionary) Machine Learning and Neuroevolution; Evolvable Hardware and Evolutionary Robotics.

Part IV: Multi-Objective Optimization; Real-World Applications.

This multi-volume LNCS set, LNCS 15148-15151, constitutes the refereed proceedings of the 18th International Conference on Parallel Problem Solving from Nature, PPSN 2024, held in Hagenberg, Austria, in September 2024.

The 101 full papers presented in these proceedings were carefully reviewed and selected from 294 submissions. The papers presented in these four volumes are organized in the following topical sections:

Part I: Combinatorial Optimization; Genetic Programming; Fitness Landscape Modeling and Analysis.

Part II: Benchmarking and Performance Measures; Automated Algorithm Selection and Configuration; Numerical Optimization; Bayesian- and Surrogate-Assisted Optimization.

Part III: Theoretical Aspects of Nature-Inspired Optimization; (Evolutionary) Machine Learning and Neuroevolution; Evolvable Hardware and Evolutionary Robotics.

Part IV: Multi-Objective Optimization; Real-World Applications.

This multi-volume LNCS set, LNCS 15148-15151, constitutes the refereed proceedings of the 18th International Conference on Parallel Problem Solving from Nature, PPSN 2024, held in Hagenberg, Austria, in September 2024.

The 101 full papers presented in these proceedings were carefully reviewed and selected from 294 submissions. The papers presented in these four volumes are organized in the following topical sections:

Part I: Combinatorial Optimization; Genetic Programming; Fitness Landscape Modeling and Analysis.

Part II: Benchmarking and Performance Measures; Automated Algorithm Selection and Configuration; Numerical Optimization; Bayesian- and Surrogate-Assisted Optimization.

Part III: Theoretical Aspects of Nature-Inspired Optimization; (Evolutionary) Machine Learning and Neuroevolution; Evolvable Hardware and Evolutionary Robotics.

Part IV: Multi-Objective Optimization; Real-World Applications.

This multi-volume LNCS set, LNCS 15148-15151, constitutes the refereed proceedings of the 18th International Conference on Parallel Problem Solving from Nature, PPSN 2024, held in Hagenberg, Austria, in September 2024.

The 101 full papers presented in these proceedings were carefully reviewed and selected from 294 submissions. The papers presented in these four volumes are organized in the following topical sections:

Part I: Combinatorial Optimization; Genetic Programming; Fitness Landscape Modeling and Analysis.

Part II: Benchmarking and Performance Measures; Automated Algorithm Selection and Configuration; Numerical Optimization; Bayesian- and Surrogate-Assisted Optimization.

Part III: Theoretical Aspects of Nature-Inspired Optimization; (Evolutionary) Machine Learning and Neuroevolution; Evolvable Hardware and Evolutionary Robotics.

Part IV: Multi-Objective Optimization; Real-World Applications.

This book explores the intersection between explainable artificial intelligence (XAI) and evolutionary computation (EC). In recent years, the fields of XAI and EC have emerged as vital areas of study within the broader domain of artificial intelligence and computational intelligence. XAI seeks to address the pressing demand for transparency and interpretability in AI systems, enabling their decision-making processes to be scrutinised and trusted. Meanwhile, EC offers robust solutions to complex optimisation problems across diverse and challenging domains, drawing upon the principles of natural evolution. While each field has made significant contributions independently, their intersection remains an underexplored area rich with transformative potential.

This book charts a path towards advancing computational systems that are transparent, reliable, and ethically sound. It aims to bridge the gap between XAI and EC by presenting a comprehensive exploration of methodologies, applications and case studies that highlight the synergies between these fields. This book will serve as both a resource and an inspiration, encouraging researchers and practitioners within XAI and EC, as well as those from adjacent disciplines, to collaborate and drive the development of intelligent computational systems that are not only powerful but also inherently trustworthy.